Simulating WideBandgap Power Circuits Using Advanced Characterization and Modeling

With the emergence of wide-bandgap (WBG) power semiconductor devices, the power electronics industry is facing multiple inflection points. For example, the high-speed operation of WBG devices has important implications for circuit simulation. This article presents one way to create simulations that surpass those developed using conventional methods.

Outlining the Emerging Challenges in Power-circuit Design

WBG power devices are expected to provide many benefits, in particular, significant improvements in power efficiency. This is especially true in automotive and industrial applications where reduced energy loss enables greater conversion efficiency. In addition, a high-frequency operation reduces the size of peripheral components such as DC-link capacitors and inductors, thereby reducing the size of power-conversion systems. Further, the ability of WBG devices to operate at higher temperatures reduces or eliminates the need for large, heavy cooling systems.

In practice, there are many obstacles on the road to these benefits. Foremost are the challenges in circuit design due to the speed of WBG devices: currently, they are 10 to 100 times faster than conventional silicon (Si) devices. Although the switching frequency of the power conversion circuit is not especially high, higher-frequency components in the switching waveform can easily cause unexpected electromagnetic interference (EMI).

While EMI is also an issue for Si-based power circuits, it is more difficult to resolve when using WBG devices. The reason: faster devices produce faster voltage changes, potentially causing false turn-on of field-effect transistors (FETs). If that happens, the resulting surge current will generate heat in the device. The worst-case scenario is the catastrophic failure of a prototype design. Within the circuit, parasitics such as stray capacitance or stray inductance can also cause problems. For example, a rapid signal change (e.g., dv/dt or di/dt) can trigger local oscillations (i.e. ringing) related to stray inductance and capacitance.

Device-modeling software can address these issues if it accurately predicts the behavior of high-speed WBG devices. Unfortunately, none of the currently available circuit-simulation software can accurately model high-speed power-conversion as performed by WBG devices.

Comparing New and Conventional Simulations

To meet this need, our organization has developed a new way to model and simulate WBG devices. Simulations of a DC-DC converter will illustrate the advantages of the new method compared to a conventional approach.

Figure 1a shows simulation results (red) plotted over measured responses (blue) for the DC-DC converter circuit. The simulation was performed using SPICE software and a conventional device model downloaded from the manufacturer’s website. All four traces show deviations dv/dt and di/dt: there are obvious time shifts, differences in peak current, and occurrences of ringing. In contrast, Figure 1b shows the results produced with the new method: there is a closer agreement between the simulated and measured traces.

Figure 1a: Comparison of the conventional simulation with measured results.

All four traces show deviations dv/dt and di/dt: there are obvious time shifts, differences in peak current, and occurrences of ringing. In contrast, Figure 1b shows the results produced with the new method: there is a closer agreement between the simulated and measured traces.

Figure 1b: Comparison of the new method with the same measurement results.

Achieving Better Simulations of WBG Devices

Device models are the essential elements of every circuit simulation. However, there is currently no standard model that accurately represents the behavior of a power device.

In any practical application of a device model, a mathematical representation that is differentiable is desirable for two reasons: it enables faster convergence of the simulation, and it is especially useful to a circuit designer who does not have access to the physical parameters. For Si devices and SiC MOSFETs, Keysight has developed a model that utilizes mathematical equations. This enhances the ability to faithfully represent device behavior across a wide range of conditions. As shown in the following sections, the equations were derived from measurements of real-world devices

Deriving a High-power IV Curve Device

Models are often created using IV curves and CV curves. In the case of a power circuit, the IV curve is the better choice. Even so, an IV curve measured using a curve tracer (through its integrated LCR meter) covers only a limited area, failing to capture the switching locus of a power circuit with an inductive load (Figure 2a).

Measuring OFF- and ON-state S-parameters

It’s important to characterize device parasitics such as drain inductance and source inductance because they are a major cause of the ringing. One of the best ways to extract the values of parasitics is to perform S-parameter measurements when the FET is in its OFF state. Although this approach is not commonly used in the power electronics industry, the resulting measurements of parasitics can improve simulation results for WBG devices.

This is a limitation of typical curve tracers that cannot supply sufficient power. Even if the instrument could deliver more power, the measurement results would be adversely affected by the heat generated by the power caused by the long pulse during the test. An alternative is a “double-pulse tester” or DPT system. Because the DPT system can perform fast pulse measurements, it can derive the high-power IV curve from measured switching characteristics (Figure 2b). With this method, the resulting IV curve covers the entire switching locus, and this enhances the quality of subsequent simulations.

The capacitances of a FET are also important, especially its gate-drain capacitance (Cgd) and gate-source capacitance (Cgs). These can be measured using an LCR meter with a drain-to-source bias. However, these measurements are made with the FET in the off state. Cgd changes when the device is on or when a gate voltage is applied (Figure 3).

Figure 3: ON-state characteristics of Cgd vary with Vgs and the test circuit.

It is possible to characterize these values using a high-current bias-T that blocks the DC current flowing into a vector network analyzer (VNA), as shown in Figure 4. Because the change in Cgd is associated with the amount of charge present during the switching process, this value is critical to an accurate simulation of the time lag in switching.

Analyzing electromagnetic effects Robust device models will significantly improve circuit simulations. However, this alone is not sufficient for accurate simulation of a power circuit. Because the in-circuit parasitics play an important role in causing ringing, surges, and so on, it is also necessary to consider parasitics in the circuit layout. Incorporating an electromagnetic (EM) analysis has an effect on the simulation results, as shown in Figure 5.

Once this level of simulation accuracy has been achieved, compatible simulation software for high-frequency designs can provide additional capabilities such as frequency-domain analyses (e.g., diagnose EMIrelated issues) and the animation of current-density profiles (Figure 6).

It is possible to characterize these values using a high-current bias-T that blocks the DC current flowing into a vector network analyzer (VNA), as shown in Figure 4. Because the change in Cgd is associated with the amount of charge present during the switching process, this value is critical to an accurate simulation of the time lag in switching.

Outlining the Solution

Figure 7 illustrates a well-rounded vision for power-circuit simulation: it encompasses measurements, modeling and simulation. A variety of measurements provide the foundation for robust simulation. For example, IV/CV and S-parameter measurement solutions provide OFF the-shelf characterization for device modeling (Keysight PD1000A and ENA Series, respectively). A dynamic-device analyzer/double-pulse tester provides the switching characterization needed for simulation verification, and it also supports the derivation of high-power IV curves (Keysight PD1500A).

Simulation software completes the vision (Keysight Pathwave ADS). The software used here has the benefit of 75 years of accumulated expertise in the creation of industry-leading RF tools. Using this type of advanced software reduces or eliminates prototyping cycles while enhancing speed and quality in the development of new power circuits.

About the Authors

Ryo Takeda worked as a business development engineer at Keysight Technologies Incorporated, a company driven to deliver breakthrough solutions and trusted insight in electronic design, test, manufacture, and optimization to help customers accelerate the innovations that connect and secure the world.

Bernhard Holzinger worked at Keysight Technologies Incorporated, a company driven to deliver breakthrough solutions and trusted insight in electronic design, test, manufacture, and optimization to help customers accelerate the innovations that connect and secure the world.

Noriyoshi Hashimoto worked as an application engineer at Keysight Technologies Incorporated, a company driven to deliver breakthrough solutions and trusted insight in electronic design, test, manufacture, and optimization to help customers accelerate the innovations that connect and secure the world.

“Circuit Simulation of a Silicon-Carbide MOSFET Considering the Effect of the Parasitic Elements on Circuit Boards by Using S-parameters,” IEEE Applied Power Electronics Conference and Exposition (APEC), pp. 2875-2878, 2018